ML4H Process and Content Management System
A unified modelling framework to address the problem of conceptual mapping and semantic interoperability of product requirements of AI/ML based medical devices among various stakeholders including software developers, quality managers, medical professionals and notified bodies.
Scope
This project aims at the design and development of a process and content management system(PCMS) for regulatory good machine learning practice guidelines(GMLP). The PCM system can potentially serve as a workflow utility or tool for the healthcare AI product developers, manufactiurers and regualtors and can guide them on how to efficiently and optimally adopt the regulatory GMLPs in reducing the complexity of the requirements analysis and conformity assessment workflows.
Aims
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To develop an ontology database
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To define processes for database content update
Outputs
Collaboration resources
You are welcome to inquire about the work stream and opporunities for collaboration directly with the work stream team.
- General contact Christian Johner, christian.johner@johner-institut.de / Pradeep Balachandran, pradeep@aiaudit.org
Meetings
Regular meetings for this work stream take place at the below coordinates.
- Meetings Bi-weekly Tuesday, 2.00 PM, CET
- Zoom room Click here to join meeting
Communication
You can subsbscribe to the work stream mailing list to receive updates and join the asynchronous group chat.
- Group chat https://daisamreggmlp-inx4514.slack.com
- Mailing list
Tools
We use different tools in our remote work. They include shared documents, github projects for code as well as task tracking and a collaborative whiteboard for ideation. You can request access via the below links.
- Shared drive
- Github project
- Collaborative whiteboard
You can find more information about the way we usually carry out our work remotely in teams here.
Milestones
Important reference material
This is a list of related work and resources relevant for this work stream. It comprises resources the work stream contributors consider good practice.